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CAR (Cadastro Ambiental Rural)

marketplace

The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them. Covers capability requests like "find an MCP that does X", "consulta um CPF", "is there a tool for Y". Core flow: action=search discovers MCPs by intent → describe returns one MCP's full profile (every tool with its id + params, pricing, auth) so you pick the right tool_id → invoke RUNS that tool. KEY: invoke works even when the MCP is NOT installed — it runs the tool pontualmente (one-off), without adding the MCP to the toolkit and without bloating the tool list. If the MCP needs a credential/login, invoke returns a connect link; if it is paid and the wallet is empty, invoke returns a checkout/top-up link (the user opens it, then you retry). Use install only to make an MCP PERMANENT in the active toolkit (its tools then show up natively in future sessions); prefer invoke for a single/occasional use. list_tools lists what is callable right now. subscribe/cancel handle per-MCP billing; report_bug sends feedback; request_mcp asks us to build a NEW MCP when nothing fits. Search/describe flag installed_in_toolkit vs installed_in_workspace. Writes (install/uninstall/subscribe/cancel and the one-off install behind invoke) require workspace owner/admin. It also carries the mcp.ai PROMPT LIBRARY, which is about ready-made prompt TEXT rather than MCPs: search_prompts finds one, get_prompt returns its full text with {{variables}} filled, and publish_prompt saves a prompt and returns a shareable mcp.ai/p/ link that opens without login.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryNo
actionNosearch
mcp_idNo
messageNo
tool_idNo
argumentsNo{}
immediateNo
tier_slugNo
prompt_bodyNo
prompt_slugNo
prompt_toolNo
prompt_varsNo{}
conversationNo[]
prompt_titleNo
request_nameNo
cancel_reasonNo
cancel_commentNo
prompt_targetsNo
report_contextNo
prompt_categoryNo
request_detailsNo
prompt_descriptionNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description discloses critical behavioral traits beyond annotations: invoke runs uninstalled MCPs one-off, returns connect/checkout links on auth/payment failures, and requires owner/admin for writes. No contradiction with annotations (readOnlyHint=false, destructiveHint=false). This gives the agent operational details needed to anticipate side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single dense paragraph (~300 words) with no headers or bullet points. It is front-loaded with the main purpose but becomes a wall of text, repeating invoke/install advice and mixing the MCP marketplace and prompt library topics. While the content is valuable, the structure hampers quick scanning.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers most actions, permissions, prompt library, and even error flows (connect/checkout links). However, it omits the `resume` action entirely and provides no details on output formats or pagination, which are important for a tool with no output schema. It is highly complete for core usage but not exhaustive.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema coverage, the description compensates by explaining key parameters: `action` (all enumerated values), `tool_id` (used by invoke), `arguments`, and prompt parameters like `prompt_slug`, `prompt_vars`, and `prompt_body`. However, many parameters (limit, immediate, tier_slug, cancel_reason, etc.) are never mentioned, leaving gaps. Still, it adds substantial meaning for the core flow.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It also explains the core flow (search → describe → invoke) and distinguishes marketplace actions from the sibling tools (e.g., report_bug, toolkit_info). This is a specific, verb-driven purpose that leaves no ambiguity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit when-to-use guidance, e.g., 'Use install only to make an MCP PERMANENT in the active toolkit... prefer invoke for a single/occasional use.' It also defines the core flow and states that writes require workspace owner/admin. This clearly tells an agent when to use each action versus alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3.3/5.0
Disambiguation2/5

The tool set is a confusing mix of generic platform operations (marketplace, connect, toolkit_info, report_bug, show_version, authenticate) and one domain-specific tool (car_ambiental_rural_consultar). Several platform tools have overlapping or unclear boundaries: marketplace also lists installed tools, overlapping with toolkit_info; authenticate and connect both deal with authentication status. The single CAR tool stands out as unrelated to the rest, making it hard for an agent to know which tool to pick for a given task.

Naming Consistency1/5

Tool naming is highly inconsistent: mixed languages (English 'authenticate', Portuguese 'car_ambiental_rural_consultar'), mixed casing (camelCase 'authenticate', 'marketplace' versus snake_case 'car_ambiental_rural_consultar', and multi-word compounds 'show_version', 'toolkit_info', 'report_bug'). There is no discernible verb_noun pattern or consistent style across the set.

Tool Count2/5

While 7 tools is a reasonable count for a typical server, this server is named 'CAR' but only one of the seven tools actually relates to CAR. The other six are generic platform administration tools that would be expected in a completely different server (e.g., an MCP.AI toolkit management server). The count is thus inappropriate for the server's stated domain, as the majority of tools are out of place.

Completeness2/5

For a server ostensibly about CAR (Cadastro Ambiental Rural), the only domain tool is a single consult operation. There is no coverage for other plausible CAR workflows (e.g., listing properties, updating data, or exporting information). The remaining platform tools are unrelated to CAR, so the domain surface is severely incomplete. Even if the intended scope is solely 'consult,' the presence of many unrelated tools makes the completeness of the set as a whole poor.